Obesity has risen to epidemic proportions in recent decades. The relative Constance of human biology suggest that changes in the environment, particularly in relation to food consumption, account for these increases in BMI. Further, the inability of individually-based treatments to have a long term impact on obesity encourage the study of environmentally-based approaches. The "stop-light" approach categorizes foods into color-coded groups according to caloric content and has been used effectively with children but is yet to be tested with adults. The primary aim of this study is to determine whether a simplified, color-coded food categorization system, based on energy density (ED; calories per gram), has an effect on adult food purchasing in a large supermarket in NY. Evidence demonstrates that, when individuals purchase and consume more low ED foods, they consume less high ED foods, and reduce overall caloric intake. This study will test the hypothesis that this simplified food categorization system will increase purchasing of low ED foods and decrease purchasing of high ED foods, especially in those with the highest BMI. METHODS: S's will be 140 overweight M and F recruited at a D'Agostino's supermarket at in NY. Individual purchasing will be tracked through scan card technology used at all D'Agostino's. ED will be calculated for 500 food items randomly selected from the inventory database. Items will be categorized in either low or high ED groups and marked with blue or orange dots (respectively). There will also be a decoy color (Green) placed on 250 randomly selected items. Color markings will be placed on item labels located on the shelving beneath each item 1 mo prior to recruitment. Demographic information (including self-reported body weight) will be collected and S's will be randomized to an experimental or control group. Experimental S's will receive a card describing the food categorization system: Blue = LOW CALORIE (eat more); Orange = HIGH CALORIE (eat less); Green = DECOY (ignore). De-identified purchasing data for all S's will be analyzed for 12 wk prior to intervention (retrospectively retreived from the D'Agostino database) to establish baseline purchasing behavior. Following randomization, 12 wk of purchasing data will be collected. Selfreported weight at the end of 12 wk will be obtained through phone calls. Cross-sectional comparisons [unreadable] between the different food categories (ED groups) will be performed across intervention periods between [unreadable] groups. PUBLIC HEALTH RELEVANCE: If positive results are obtained, a similar system of food categorization could be implemented in supermarkets easily and inexpensively. If supermarkets nationwide were willing to implement this system, even a small statistical effect may have a clinically significant effect in combating the [unreadable] [unreadable] [unreadable] [unreadable]